Any problems? a wearable sensor-based platform for representational learning-analytics
| Autor: | Sebastian Gröber, Bernhard Sick, Gerald Pirkl, Pascal Klein, Jochen Kuhn, Peter Hevesi, Paul Lukowicz, Carina Heisel |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
business.industry
Computer science media_common.quotation_subject Learning analytics Wearable computer 02 engineering and technology Affect (psychology) Gaze 03 medical and health sciences 0302 clinical medicine Human–computer interaction Reading (process) Adaptive system ComputingMilieux_COMPUTERSANDEDUCATION 0202 electrical engineering electronic engineering information engineering Key (cryptography) Virtual learning environment Eye tracking 020201 artificial intelligence & image processing Computer vision Artificial intelligence business 030217 neurology & neurosurgery media_common |
| Zdroj: | UbiComp Adjunct |
| Popis: | We describe in this work a sensor-based learning platform which supports both the teacher and the learner during exercises. We use a combination of eye tracker, sensor pen and exercise texts to capture the progress of learners. The eye tracker retrieves information about the gaze, for example reading or scanning for key words; the sensor pen captures trends like number of words or the pressure applied to the paper. Combining this information, the platform should be used to indicate problems of the learner to the teacher. Besides presenting the data information to the teacher, we work on advancing the platform to an adaptive system, which could give individual feedback to the learners themselves according to their individual cognitive and affective requirements. |
| Databáze: | OpenAIRE |
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